class   lowercase_       :



							def __init__(		self							):
													_snake_case		:	List[str]							=       {}  # Mapping from char to TrieNode
													_snake_case		:	Any							=       False



							def 			UpperCamelCase			(		self ,							lowercase_							):

													for word in words:
																			self.insert(UpperCamelCase_							)



							def 			UpperCamelCase			(		self ,							lowercase_							):
													_snake_case		:	List[str]							=       self
													for char in word:
																			if char not in curr.nodes:
																									_snake_case		:	Tuple							=       TrieNode()
																			_snake_case		:	List[str]							=       curr.nodes[char]
													_snake_case		:	Union[str, Any]							=       True



							def 			UpperCamelCase			(		self ,							lowercase_							):
													_snake_case		:	int							=       self
													for char in word:
																			if char not in curr.nodes:
																									return False
																			_snake_case		:	Any							=       curr.nodes[char]
													return curr.is_leaf



							def 			UpperCamelCase			(		self ,							lowercase_							):

													def _delete(lowercase_ ,							lowercase_ ,							lowercase_							) -> bool:
																			if index == len(UpperCamelCase_							):
																									# If word does not exist
																									if not curr.is_leaf:
																															return False
																									_snake_case		:	Optional[int]							=       False
																									return len(curr.nodes							) == 0
																			_snake_case		:	int							=       word[index]
																			_snake_case		:	Union[str, Any]							=       curr.nodes.get(UpperCamelCase_							)
																			# If char not in current trie node
																			if not char_node:
																									return False
																			# Flag to check if node can be deleted
																			_snake_case		:	Optional[Any]							=       _delete(UpperCamelCase_ ,							UpperCamelCase_ ,							index + 1							)
																			if delete_curr:
																									del curr.nodes[char]
																									return len(curr.nodes							) == 0
																			return delete_curr

													_delete(self ,							UpperCamelCase_ ,							0							)




def    snake_case		(__lowercase   ,     __lowercase		)			->			None:

						'''simple docstring'''



						if node.is_leaf:
												print(__snake_case   ,     end=" "		)

						for key, value in node.nodes.items():
												print_words(__snake_case   ,     word + key		)
def    snake_case		()			->			bool:

						'''simple docstring'''



						_snake_case		:	Dict							=       "banana bananas bandana band apple all beast".split()
						_snake_case		:	Union[str, Any]							=       TrieNode()
						root.insert_many(__snake_case		)
						# print_words(root, "")
						assert all(root.find(__snake_case		) for word in words		)
						assert root.find("banana"		)
						assert not root.find("bandanas"		)
						assert not root.find("apps"		)
						assert root.find("apple"		)
						assert root.find("all"		)
						root.delete("all"		)
						assert not root.find("all"		)
						root.delete("banana"		)
						assert not root.find("banana"		)
						assert root.find("bananas"		)
						return True
def    snake_case		(__lowercase   ,     __lowercase		)			->			None:

						'''simple docstring'''



						print(str(__snake_case		)   ,     "works!" if passes else "doesn\'t work :("		)
def    snake_case		()			->			None:

						'''simple docstring'''



						assert test_trie()
def    snake_case		()			->			None:

						'''simple docstring'''



						print_results("Testing trie functionality"   ,     test_trie()		)


if __name__ == "__main__":
				main()







"""simple docstring"""
import argparse
import json
import os

from tensorflow.core.protobuf.saved_model_pba import SavedModel


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
snake_case : Optional[Any]     		=		"""."""

# Internal TensorFlow ops that can be safely ignored (mostly specific to a saved model)
snake_case : List[str]     		=		[
    """Assert""",
    """AssignVariableOp""",
    """EmptyTensorList""",
    """MergeV2Checkpoints""",
    """ReadVariableOp""",
    """ResourceGather""",
    """RestoreV2""",
    """SaveV2""",
    """ShardedFilename""",
    """StatefulPartitionedCall""",
    """StaticRegexFullMatch""",
    """VarHandleOp""",
]


def 							A						(				__snake_case: Optional[Any] ,     __snake_case: Tuple ,     __snake_case: Any  )    ->		int:

       """simple docstring"""





       __magic_name__      				=    SavedModel()
       __magic_name__      				=    []

       with open(os.path.join(__snake_case ,     'utils' ,     'tf_ops' ,     'onnx.json'  )  ) as f:
              __magic_name__      				=    json.load(__snake_case  )['opsets']

       for i in range(1 ,     opset + 1  ):
              onnx_ops.extend(onnx_opsets[str(__snake_case  )]  )

       with open(__snake_case ,     'rb'  ) as f:
              saved_model.ParseFromString(f.read()  )

       __magic_name__      				=    set()

       # Iterate over every metagraph in case there is more than one (a saved model can contain multiple graphs)
       for meta_graph in saved_model.meta_graphs:
              # Add operations in the graph definition
              model_op_names.update(node.op for node in meta_graph.graph_def.node  )

              # Go through the functions in the graph definition
              for func in meta_graph.graph_def.library.function:
                     # Add operations in each function
                     model_op_names.update(node.op for node in func.node_def  )

    # Convert to list, sorted if you want
       __magic_name__      				=    sorted(__snake_case  )
       __magic_name__      				=    []

       for op in model_op_names:
              if op not in onnx_ops and op not in INTERNAL_OPS:
                     incompatible_ops.append(__snake_case  )

       if strict and len(__snake_case  ) > 0:
              raise Exception(F"""Found the following incompatible ops for the opset {opset}:\n""" + incompatible_ops  )
       elif len(__snake_case  ) > 0:
              print(F"""Found the following incompatible ops for the opset {opset}:"""  )
              print(*__snake_case ,     sep='\n'  )
       else:
              print(F"""The saved model {saved_model_path} can properly be converted with ONNX."""  )


if __name__ == "__main__":
 snake_case : Optional[Any]     		=		argparse.ArgumentParser()
 parser.add_argument("""--saved_model_path""", help="""Path of the saved model to check (the .pb file).""")
 parser.add_argument(
     """--opset""", default=1_2, type=int, help="""The ONNX opset against which the model has to be tested."""
 )
 parser.add_argument(
     """--framework""", choices=["""onnx"""], default="""onnx""", help="""Frameworks against which to test the saved model."""
 )
 parser.add_argument(
     """--strict""", action="""store_true""", help="""Whether make the checking strict (raise errors) or not (raise warnings)"""
 )
 snake_case : Any     		=		parser.parse_args()

 if args.framework == "onnx":
  onnx_compliancy(args.saved_model_path, args.strict, args.opset)